Obviously, a comprehensive drug control program should target both typical users and hard-core users. The relative effectiveness of targeting typical versus hard-core users will probably vary according to several factors (MacCoun, 1998). Everything else being equal, it will be more effective to target typical users when the dose-response curve rises very quickly with small doses and when the statistical distribution of consumption is fairly symmetric. It should be added that reducing typical users can also be effective as an attempt to decrease the eventual number of hard-core users. It will be more effective to target heavy users when the dose-response curve rises slowly at low doses and when the statistical distribution of consumption is heavily skewed. Thus the ability to create accurate dose-response curves promises benefits for reduced consumption of illegal drugs.

Reciprocal Effects of Drug-Related Harms on Levels of Use

Complicating any analysis of the relationship between drug use patterns and drug-related harms is the possibility that the risks of drug use have a reciprocal causal influence on the prevalence, incidence, and quantity of drug use. The decision to use, or to escalate, illegal drug use may not reflect a purely rational risk calculation (see MacCoun, 1993), but it seems likely that both potential users and current users are influenced by their perceptions of the risks—health risks, legal risks, and social risks. Still, evidence on this point is surprisingly ambiguous. Analyses of Monitoring the Future data consistently show a negative correlation between the perceived riskiness of drugs and the likelihood of their use (Bachman et al., 1998), but the causal direction of this correlation is not clear.

Musto (1971, 1987) and Johnston (1991) have each proposed a “generational forgetting” account of drug epidemics, in which the risks and disorder associated with the use of a drug become increasingly visible, triggering a reduction in initiation. As the number and visibility of users declines over time, this risk information becomes less accessible, and initiation begins to rise again, renewing the cycle. This model is plausible but largely untested. There are simply too few cycles of data to test the model, much less establish the cyclical nature of drug epidemics. On the surface at least, the generational forgetting model also conflicts with another piece of conventional wisdom in drug policy circles—the contention that providing risk information is relatively ineffective as a strategy for discouraging drug use (discussed in Chapter 7). But it is possible that direct observation of hard-core users has a discouraging effect that is more powerful or more credible than classroom-based risk information (see Fazio et al., 1978; Feldman, 1968).



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